Risk-O-Meter: An Intelligent Clinical Risk Calculator

We present a system called Risk-O-Meter to predict and analyze clinical risk via data imputation, visualization, predictive modeling, and association rule exploration. Clinical risk calculators provide information about a person's chance of having a disease or encountering a clinical event. Such tools could be highly useful to educate patients to understand and monitor their health conditions. Unlike existing risk calculators that are primarily designed for domain experts, Risk-O-Meter is useful to patients who are unfamiliar with medical terminologies, or providers who have limited information about a patient. Risk-O-Meter is designed in a way such that it is exible enough to accept limited or incomplete data inputs, and still manages to predict the clinical risk effciently and effectively. Current version of Risk-O-Meter evaluates 30-day risk of hospital readmission. However, the proposed system framework is applicable to general clinical risk predictions. In this demonstration paper, we describe different components of Risk-O-Meter and the intelligent algorithms associated with each of these components to evaluate risk of readmission using incomplete patient data inputs.
Conference: 
19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), Chicago, IL
Year: 
2013
Authors: 
K. Zolfaghar, J. Agarwal, D. Sistla, S.-C. Chin, S. Basu Roy, and N. Verbiest
Publication File: